Justyna Petke

Justyna Petke is a Principal Research Fellow and Proleptic Senior Lecturer (Associate Prof.), conducting research in genetic improvement. She has a doctorate in Computer Science from University of Oxford and is now at the Centre for Research on Evolution, Search and Testing (CREST) in University College London. She has published on applications of genetic improvement. Her work on the subject was awarded a Silver and a Gold ’Humie’ at GECCO 2014 and GECCO 2016 as well as an ACM SIGSOFT Distinguished Paper Award at ISSTA 2015. She was the PC co-Chair for the International Symposium on Search-Based Software Engineering in 2017. She also organised six Genetic Improvement Workshops. She currently serves on the editorial board of the Genetic Programming and Evolvable Machines journal.

Bobby R. Bruce

Bobby Bruce is a Postdoctoral Scholar at UC Davis where he primarily works on the gem5 computer architecture simulator. Prior to UC Davis, Bobby carried out research into the automatic optimization of Java bytecode at UCLA. His research interests are centred around Search-based Software Engineering, and its application to improving software performance.

Yu Huang

Yu Huang is a PhD candidate at the University of Michigan, Ann Arbor. Her research includes applying GI-based automated program repair (APR) techniques in embedded systems and human factors in software automation with a focus on human bias against automated tools in code review. She has served as the organizer for multiple Diversity, Equivalence and Inclusion events hosted at University of Michigan. She was also in charge of the social media for GI 2020 to advertise the event and connect researchers and practitioners in the community. Currently she is serving as the Social Media Chair for GI 2021.

Aymeric Blot

Aymeric Blot is a Research Associate conducting research in genetic improvement at the CREST and SOLAR groups in University College London. He received in 2018 a doctorate from the University of Lille following work on automated algorithm design for multi-objective combinatorial optimisation. His research focuses on strengthening GI techniques using knowledge from automated machine learning, algorithm configuration, and evolutionary computation. He maintains and evolves the community website on genetic improvement.

Westley Weimer

Westley Weimer is a Professor at the University of Michigan He received his PhD from the University of California at Berkeley. His research interests include reducing the costs associated with software development at scale (particularly through automated program repair) as well as program analysis, formal verification, and human linguistic and visual interaction with software. He is a senior member of the Association for Computing Machinery and his work has led to over eleven thousand citations and several awards, including three ‘Humies’ and ICSE 2019 Most Influential paper for his work on using Genetic Improvement for bug fixing. He also organised five Genetic Improvement workshops.